The family and socio-economic circumstances of children's parents at birth and during the childrearing years are fundamental determinants of children's health and well-being. This study's overall objective is to develop statistical methods for combining surveys and population data collections (especially of births and marital and non-marital unions) for the improved estimation of these birth and childhood circumstances. Specific aims are to (1) Develop and test statistical methods to combine multiple sources of survey data and population data; (2) Improve estimates of the parameters of fertility and marital and non-marital union regression equations, and of simulated life-course fertility and union duration measures; and (3) to expand and disseminate the statistical capabilities to the demographic community. It will be shown that combining population and survey data in the estimation allows for more modeling detail than when using population data alone, and more precise estimates than when using survey data alone. Further statistical development will allow for survey data to be combined from more than one data set, thereby obtaining some of the same benefits as from combining survey and population data. Methods for incorporating degrees of inaccuracy in the population data, and imperfect matches between the population collection and the survey's sampling frame and collection methods, will also be developed and applied. Comparative applications of the methods between the U.S. and the U.K. will be made to explore their advantages and challenges over a greater range of population data collection types than available in the U.S. alone. Applications across multiple developed countries will demonstrate that methods for combining survey and population data can be used to overcome the otherwise severe restrictions placed on cross-national comparisons.